Get yourself trained on Mathematics for Data with this Online Training Mathematics for Data Science and Machine Learning using R.
Online Training Mathematics for Data Science and Machine Learning using R
With the increase of data by each passing day, Data Science has become one of the most important aspects in most of the fields. From healthcare to business, everywhere data is important. However, it revolves around 3 major aspects i.e. data, foundational concepts and programming languages for interpreting the data. This course teaches you everything about all the foundational mathematics for Data Science using R programming language, a language developed specifically for performing statistics, data analytics and graphical modules in a better way.Why Learn Foundational mathematical Concepts for Data Science Using R?Data Science has become an interdisciplinary field which deals with processes and systems used for extracting knowledge or making predictions from large amounts of data. Today, it has become an integral part of numerous fields resulting in the high demand of professionals of data science. From helping brands to understand their customers, solving complex IT problems, to its usability in almost every other field makes it very important for the functioning and growth of any organizations or companies. Depending upon the location the average salary of data scientist expert can be over $120,000. This course will help you learn the concepts the correct way.Why You Should Take This Online Tutorial?Despite the availability of several tutorials on data science, it is one of the online guides containing hand-picked topics on the concepts for foundational mathematics for Data Science using R programming language. It includes myriads of sections (over 9 hours of video content) lectured by Timothy Young, a veteran statistician and data scientists . It explains different concepts in one of the simplest form making the understanding of Foundational mathematics for Data Science very easy and effective.This Course includes:Overview of Machine Learning and R programming languageLinear Algebra- Scalars, vectors & MetricesVector and Matrix OperationsLinear RegressionCalculus- Tangents, Derivatives and othersVector Calculus- Vector spaces, Gradient Descent and othersSo Much More!This field is constantly become important for both industries as well as developers. If you are one of those who loves data science and are having issues with all the foundational concepts related to it, then its the right online tutorial to solve your issues. Start today, in order to become the expert of tomorrow!
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.